Interpretive Summary: For a significant portion of the growth cycle of agricultural crops and in most arid and semiarid rangeland ecosystems, vegetation cover is sparse or below 50%. This means the soil surface plays an important role in total water use or evapotranspiration for many landscapes. A two-source energy balance model developed to use remote sensing data for computing water and energy fluxes from soil and vegetative canopies has been applied successfully to a wide range of vegetation cover conditions. By explicitly treating the energy fluxes from the soil and vegetation, the model is well suited for sparse-canopied covered surfaces. Several recent modifications have been made to the model to account for some of the unique properties associated with sparse canopies. One of these changes involves use of a more physically-based algorithm for predicting the radiation absorbed by the soil and vegetation. Another is a simple method to account for vegetation being clumped, such as row crops, which affects both the wind and radiation penetration inside the canopy. Model results with and without these modifications are compared using data collected from a sparsely vegetated row crop of cotton. It is suggested that these two new algorithms be incorporated in any two-source model applied to sparse canopies. These algorithms will lead to more accurate estimates of plant water use and assessment of vegetation stress, which will ultimately lead to better irrigation and water management decisions.

Technical Abstract:
A two-source energy balance model developed to use remotely sensed surface temperature for computing heat fluxes from soil and vegetative canopies has been applied successfully to a wide range of vegetation cover conditions. By explicitly treating the energy fluxes from the soil and vegetation, the model is well suited for sparse-canopied surfaces. Several recent modifications have been made to the model to account for some of the uniqu properties associated with sparse canopies. Two of these changes involve algorithms predicting the divergence of net radiation inside the canopy and how to account for clumped vegetation, which affects both the wind and radiation penetration inside the canopy. Model results with and without these modifications are compared using data collected from a sparsely vegetated row crop of cotton. It is suggested that these two new algorithms be incorporated in any two-source model applied to sparse canopies.